Tracking files in the kepler provenance framework

Pierre Mouallem, Roselyne Barreto, Scott Klasky, Norbert Podhorszki, Mladen Vouk

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

13 Scopus citations

Abstract

Workflow Management Systems (WFMS), such as Kepler, are proving to be an important tool in scientific problem solving. They can automate and manage complex processes and huge amounts of data produced by petascale simulations. Typically, the produced data need to be properly visualized and analyzed by scientists in order to achieve the desired scientific goals. Both run-time and post analysis may benefit from, even require, additional meta-data - provenance information. One of the challenges in this context is the tracking of the data files that can be produced in very large numbers during stages of the workflow, such as visualizations. The Kepler provenance framework collects all or part of the raw information flowing through the workflow graph. This information then needs to be further parsed to extract meta-data of interest. This can be done through add-on tools and algorithms. We show how to automate tracking specific information such as data files locations.

Original languageEnglish
Title of host publicationScientific and Statistical Database Management - 21st International Conference, SSDBM 2009, Proceedings
Pages273-282
Number of pages10
DOIs
StatePublished - 2009
Event21st International Conference on Scientific and Statistical Database Management, SSDBM 2009 - New Orleans, LA, United States
Duration: Jun 2 2009Jun 4 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5566 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference21st International Conference on Scientific and Statistical Database Management, SSDBM 2009
Country/TerritoryUnited States
CityNew Orleans, LA
Period06/2/0906/4/09

Keywords

  • Data Provenance
  • Data Tracking
  • Scientific Data Management
  • Scientific Workflows

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